Running 29 high-performing McDonald’s locations is no small feat. For The Fonseca Group, the challenge wasn’t ambition—it was consistency.

With complex labor laws across New York and New Jersey, evolving Fair Workweek requirements, and dozens (sometimes hundreds) of scheduling warnings per location, managers were spending hours building schedules… only to spend even more time fixing them.

At its worst, schedules could generate up to 300 warnings, creating confusion, delays, and downstream operational issues—especially for newer managers. That’s when they introduced Salli, an AI assistant designed specifically for frontline restaurant operations.

The impact was immediate.

Schedules that once took hours to finalize could now be fixed in seconds. Managers no longer had to guess what warnings meant or how to resolve them—Salli guided them in real time.

The results speak for themselves:

• Schedule publish time dropped from 25.6 minutes to just 8.6 minutes (nearly 3x faster)
• Warnings reduced from hundreds to near zero valid issues in some locations
• Faster onboarding with no formal training required
• Stronger compliance across complex labor environments

But the biggest shift wasn’t just speed—it was confidence.

Salli didn’t behave like a typical chatbot. It acted as an operational co-pilot, helping managers understand why something was wrong and how to fix it. That meant better decisions, more consistency across locations, and less reliance on supervisors.

As one leader put it simply: “Speed and accuracy. Those are the two biggest changes.” And this is just the beginning.

The Fonseca Group is already looking beyond scheduling—toward a future where managers can instantly access real-time labor data, performance insights, and operational guidance, all in one place.

So what made them confident enough to roll this out across all 29 locations? And what did they discover during the beta that changed how they think about AI in restaurant operations?

👉 Read the full case study to see how it all came together.